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We present the first results from a new backend on the Australian Square Kilometre Array Pathfinder, the Commensal Realtime ASKAP Fast Transient COherent (CRACO) upgrade. CRACO records millisecond time resolution visibility data, and searches for dispersed fast transient signals including fast radio bursts (FRB), pulsars, and ultra-long period objects (ULPO). With the visibility data, CRACO can localise the transient events to arcsecond-level precision after the detection. Here, we describe the CRACO system and report the result from a sky survey carried out by CRACO at 110-ms resolution during its commissioning phase. During the survey, CRACO detected two FRBs (including one discovered solely with CRACO, FRB 20231027A), reported more precise localisations for four pulsars, discovered two new RRATs, and detected one known ULPO, GPM J1839 
$-$10, through its sub-pulse structure. We present a sensitivity calibration of CRACO, finding that it achieves the expected sensitivity of 11.6 Jy ms to bursts of 110 ms duration or less. CRACO is currently running at a 13.8 ms time resolution and aims at a 1.7 ms time resolution before the end of 2024. The planned CRACO has an expected sensitivity of 1.5 Jy ms to bursts of 1.7 ms duration or less and can detect 
$10\times$ more FRBs than the current CRAFT incoherent sum system (i.e. 0.5 
$-$2 localised FRBs per day), enabling us to better constrain the models for FRBs and use them as cosmological probes.
We present observations of the four 
$^2 \Pi _{3/2}\,J=3/2$ ground-rotational state transitions of the hydroxyl molecule (OH) along 107 lines of sight both in and out of the Galactic plane: 92 sets of observations from the Arecibo telescope and 15 sets of observations from the Australia Telescope Compact Array (ATCA). Our Arecibo observations included off-source pointings, allowing us to measure excitation temperature (
$T_{\rm ex}$) and optical depth, while our ATCA observations give optical depth only. We perform Gaussian decomposition using the Automated Molecular Excitation Bayesian line-fitting Algorithm ‘Amoeba’ (Petzler, Dawson, & Wardle 2021, ApJ, 923, 261) fitting all four transitions simultaneously with shared centroid velocity and width. We identify 109 features across 38 sightlines (including 58 detections along 27 sightlines with excitation temperature measurements). While the main lines at 1665 and 1667 MHz tend to have similar excitation temperatures (median 
$|\Delta T_{\rm ex}({\rm main})|=0.6\,$K, 84% show 
$|\Delta T_{\rm ex}({\rm main})|<2\,$K), large differences in the 1612 and 1720 MHz satellite line excitation temperatures show that the gas is generally not in LTE. For a selection of sightlines, we compare our OH features to associated (on-sky and in velocity) Hi cold gas components (CNM) identified by Nguyen et al. (2019, ApJ, 880, 141) and find no strong correlations. We speculate that this may indicate an effective decoupling of the molecular gas from the CNM once it accumulates.
We present the most sensitive and detailed view of the neutral hydrogen (
${\rm H\small I}$) emission associated with the Small Magellanic Cloud (SMC), through the combination of data from the Australian Square Kilometre Array Pathfinder (ASKAP) and Parkes (Murriyang), as part of the Galactic Australian Square Kilometre Array Pathfinder (GASKAP) pilot survey. These GASKAP-HI pilot observations, for the first time, reveal 
${\rm H\small I}$ in the SMC on similar physical scales as other important tracers of the interstellar medium, such as molecular gas and dust. The resultant image cube possesses an rms noise level of 1.1 K (
$1.6\,\mathrm{mJy\ beam}^{-1}$) 
$\mathrm{per}\ 0.98\,\mathrm{km\ s}^{-1}$ spectral channel with an angular resolution of 
$30^{\prime\prime}$ (
${\sim}10\,\mathrm{pc}$). We discuss the calibration scheme and the custom imaging pipeline that utilises a joint deconvolution approach, efficiently distributed across a computing cluster, to accurately recover the emission extending across the entire 
${\sim}25\,\mathrm{deg}^2$ field-of-view. We provide an overview of the data products and characterise several aspects including the noise properties as a function of angular resolution and the represented spatial scales by deriving the global transfer function over the full spectral range. A preliminary spatial power spectrum analysis on individual spectral channels reveals that the power law nature of the density distribution extends down to scales of 10 pc. We highlight the scientific potential of these data by comparing the properties of an outflowing high-velocity cloud with previous ASKAP+Parkes 
${\rm H\small I}$ test observations.
